JP7046490B2 - Identification of subdivided signals - Google Patents

Description

(Mutual reference of related applications)
This application claims the benefit of US Patent Provisional Application No. 62 / 278,676 (filed January 14, 2016), which is referred to in its entirety as it is described in its entirety. Incorporated by. This application is filed on January 12, 2017, and is filed in US Patent Application No. 15 / 404,228 (the title of the invention is "Region of Interest Focal Source Detection Of RS Wave Magnitudes". "Complexes"), US Patent Application No. 15 / 404,225 (invention name "Region of Interest Rotational Activity Pattern Detection"), US Patent Application No. 15 / 404, 226 (invention name "Overall System Regions of Interest ”), US Patent Application No. 15 / 404,231 (Invention title“ Non-Overlapping Loop-Type or Spirit-Type Catherator To Determine Activation Division Patent Application, US Patent Application, Section 15 / 404,266 (the name of the invention "Region of Interest Focal Source Detection") is incorporated by reference as they are described in their entirety.

(Field of invention)
The present invention relates to a system and method for determining a region of interest for ablation for the treatment of cardiac arrhythmias such as atrial fibrillation. More specifically, the present invention relates to improved intracardiac electrocardiogram (ECG) signal analysis for improving the activation map and better determining the region of interest.

Cardiac arrhythmias include various types of abnormal or irregular heartbeat rhythms, such as atrial fibrillation (AF), which is characterized by rapid and irregular heartbeats. In a normal heart, electricity starts from the chamber above the heart (ie, the atrioventricular node), passes through the atrioventricular node (AV) node, and travels through the chamber below the paired heart (ie, the ventricle). The pulse (ie, the signal) causes the heartbeat. When the signal passes through the atrioventricular node, the atrioventricular node contracts, sending blood to the ventricle through the AV node. This causes contraction of the ventricles and blood is supplied from the heart to the body. However, during the AF state, the atrial signal is disturbed, causing an irregular heartbeat.

AF can adversely affect the physical, psychological and emotional qualities of human life. AF can gradually increase in severity and frequency and, if left untreated, can lead to chronic fatigue, congestive heart failure, or stroke. Types of AF treatment include prescription drugs such as sinus rhythm maintenance drugs and drugs used to manage the high risk of stroke. These drugs should be taken daily indefinitely. Another type of AF treatment is the cardio version, which attempts to restore normal cardiac rhythm by giving an electric shock to the heart through electrodes placed in the chest. For some persistent types of AF, the cardio version is ineffective or untriviable.

Recent approaches to treating AF are minimally invasive ablation procedures (eg, catheter ablation) that ablate the heart tissue to cut off electrical pathways and block abnormal electrical impulses that can cause cardiac dysrhythmia. Can be mentioned.

One method can be used to determine one or more regions of interest for cardiac ablation using subdivision. For example, the method may use one or more sensors to detect an electrocardiogram (ECG) signal. Each ECG signal detected may indicate the electrical activity of the heart. The method can then determine one or more local excitement arrival times (LATs) for each of these plurality of ECG signals. Each LAT may indicate the excitement arrival time of the corresponding ECG signal.

The method can then generate one or more driver maps based on the determined one or more LATs. In addition, the method can also generate one or more perpetuator maps, each representing the electrical activity of the heart. The facilitator map and / or the permanent factor map can be used to derive the parameters, at least using subdivision. The derived parameters can then be processed and combined with the evidence of facilitators and the evidence of persistent factors. Ultimately, the method may determine the region of interest for cardiac ablation according to the subdivision used to derive evidence for facilitating factors and evidence for persistent factors.

One system can be used to determine one or more regions of interest for cardiac ablation using subdivision. The system includes a plurality of sensors, each sensor may be configured to detect a plurality of electrocardiogram (ECG) signals over time. Each ECG signal may indicate the electrical activity of the heart.

The system may include processing devices that include one or more processors. Each processor may be configured to determine one or more local excitement arrival times (LATs) for each of the plurality of ECG signals. Each LAT may indicate the excitement arrival time of the corresponding ECG signal. Each processor may generate one or more facilitator maps based on the determined one or more LATs for each of the plurality of ECG signals. Each processor can also generate one or more persistent factor maps, each representing the electrical activity of the heart.

Each processor may derive parameters from the facilitator and persistent factor maps using at least subdivision. Each processor can then process the derived parameters and combine them with the evidence of facilitators and the evidence of persistent factors. Each processor may then determine the region of interest for cardiac ablation and display the region of interest information on a display device according to the subdivisions used to derive evidence for facilitators and persistent factors.

Computer software products may include non-temporary computer-readable storage media containing computer program instructions. When executed by a computer, these instructions may cause the computer to perform one or more steps.

For example, a computer may perform the step of detecting an electrocardiogram (ECG) signal via a plurality of sensors, where each ECG signal is detected via one of the plurality of sensors and of the heart. Shows electrical activity. The computer can also perform a step of determining one or more local excitement arrival times (LATs) for each of the plurality of ECG signals, where the LATs are each of the corresponding ECG signals. Shows the time to reach excitement.

The computer software product may allow a computer to generate one or more promoter maps based on the determined one or more LATs of each of the plurality of ECG signals. The computer software product may also allow a computer to perform a step of generating one or more persistent factor maps, each representing the electrical activity of the heart.

The computer software product may allow a computer to perform a step of deriving parameters from a facilitator and perpetual factor map, at least using subdivision. The Computer Software product may allow a computer to perform a process of processing derived parameters and combining them with evidence of facilitators and persistence factors. Ultimately, the computer software product may allow the computer to perform the steps of determining the region of interest for cardiac ablation according to the subdivision used to derive evidence of facilitating factors and evidence of persistent factors.

In order to better understand the invention, reference is made to the detailed description of the invention as an example. These references should be read with the drawings below and similar components are given similar reference numbers.
FIG. 3 is a block diagram illustrating an exemplary classification of AF as used in the embodiments disclosed herein. FIG. 6 is a block diagram illustrating an exemplary system used to determine the AF ROI for ablation, as used in the embodiments disclosed herein. It is a part of a flowchart showing an exemplary method of determining an AF ROI for ablation according to an embodiment. It is a part of a flowchart showing an exemplary method of determining an AF ROI for ablation according to an embodiment. The mapping for specifying the ROI for ablation is shown. The outline of AF mapping subdivision is shown. The outline of the subdivision analysis in AF mapping for specifying the ROI for ablation is shown. The AF mapping for specifying the ablation ROI is shown. The AF mapping for specifying the ablation ROI is shown. The AF mapping for specifying the ablation ROI is shown. The AF mapping for specifying the ablation ROI is shown. The AF mapping for specifying the ablation ROI is shown. The AF mapping for detecting the subdivided IC ECG and specifying the ablation ROI is shown. The AF mapping for specifying the ROI for ablation is shown. The AF mapping for detecting the Fractionated Episode in IC ECG is shown. The AF mapping for detecting the occurrence of subdivision in IC ECG is shown. The AF mapping for detecting the occurrence of subdivision in IC ECG is shown. The AF mapping for detecting the occurrence of subdivision in IC ECG is shown. The AF mapping for detecting the occurrence of subdivision with increased specificity is shown. The overall mapping of AF mapping is shown. The overall mapping-inclination diagram of the AF mapping is shown. The overall mapping (characterization of the slope) of the AF mapping is shown. It shows the progression from the type of gradient to the type of potential. The time gates and time groupings of the primary and secondary slopes are further shown. Two examples of grouping are shown, further showing a single tilt, two tilt groups, a long double tilt group, and> two tilts. Two examples of grouping are shown, further showing a single tilt, two tilt groups, a long double tilt group, and> two tilts. A spatial-temporal analysis of the identified slopes represented as a rectangle is shown. An exemplary AF mapping spatial-temporal tilt analysis is shown. An exemplary AF mapping spatial-temporal tilt analysis is shown. An exemplary AF mapping spatial-temporal tilt analysis is shown.

Conventional methods and systems used for catheter ablation typically involve inserting a catheter that is guided to the heart through an incision in the skin. Prior to performing ablation, an intracardiac electrocardiogram (ICECG) signal of the heart is obtained from electrodes placed in different regions of the heart. This signal can be monitored and used to inform if one or more areas of the heart are causing abnormal heartbeats. However, conventional methods and systems used to determine these ablated areas are time consuming (eg, hours) and are specific (typically requiring long-term training). It depends on medical personnel with expertise and experience.

The embodiments disclosed herein use systems, devices and methods for determining a potential region of interest (ROI) that is the target of ablation. Various mapping techniques can be used to efficiently and accurately determine the electrical-physical state map of the AF substrate and the ROI of the potential ablation, spatial-temporal of the AF process. A map representing expression is provided. In the mapping technique, various parameters of the obtained IC ECG signal (eg cycle, temporal speed, RS complex, conduction velocity (CV), block and subdivision), and detected local excitement arrival time (LAT). ) To identify potential evidence of AF substrate promoters and persistent factors. The identification of potential evidence of facilitators and perpetual factors is used to provide mapping of AF substrates (eg, facilitator maps and perpetual factor maps). The mapping technique also utilizes the various parameters of the obtained IC ECG signal and the detected local excitement arrival time to potentially indicate the spatial-temporal manifestation of the AF process (eg, activation / wave map, etc.). Also includes providing CV maps, subdivision maps, voltage maps and block maps). Spatial-temporal expression mappings of the AF process can be used in addition to, or instead of, AF substrate mappings to identify potential ablation ROIs. The use of mapping techniques potentially reduces training time for AF map analysis, increases the success rate of ablation, and facilitates efficient interpretation of AF maps. For brevity, the embodiments described herein refer to systems and methods for use in the treatment of AF. However, it should be noted that embodiments can be used for the treatment of any type of cardiac arrhythmia, including various types of abnormal or irregular heartbeats.

FIG. 1 is a block diagram showing an exemplary classification of AF as used in the embodiments disclosed herein. The exemplary classification of FIG. 1 distinguishes between risk AF and non-hazard AF, and AF promoters and persistence factors, and their relative spatial-temporal patterns.

For example, as shown in FIG. 1, irregular heartbeats characteristic of AF 102 are classified as risk 104 or non-risk 106. Examples of non-dangerous AF 106 are the occurrence of paroxysmal (ie, intermittent) irregular heartbeats that usually normalize early within seconds or hours, and medical treatment of the heartbeat. Alternatively, treatment (eg, cardioversion) may include persistent, irregular heartbeat development that can be restored to a normal heart. An example of danger AF 104 is a long-lasting, persistent irregularity in which the heart is in a state of continuous AF and lasts for a long period of time (eg, over a year) where the state is considered permanent. The occurrence of heartbeat is mentioned.

Hazard AF can be classified according to the characteristics that can be derived from the IC ECG signal (eg, the area of activation). The activation region can be identified as a potential contributor to AF. As shown in FIG. 1, the risk AF is a potential promoter of AF (hereinafter, “promoter”) or a potential source of AF (hereinafter, “source”) 108, and a potential AF. Persistent Factors 110 (“Permanent Factors”) are classified according to various areas of activation. The facilitator 108 potentially contributes to AF by generating electrical pulses that stimulate and contract the heart, for example, producing fibrillatory conduction to other areas of the atrium. The area of activation to obtain (eg, in the atrium). Persistent factor 110 is also a persistent activation region (eg, an electrophysiological process / substrate) that can potentially contribute to AF.

Promoting factors 108 and persistent factors 110 can be represented (eg, mapped) according to their spatial-temporal expression. As shown in FIG. 1, the promoting factor 108 and the permanent factor 110 are a focal source (focal point) 112 and a localized rotational activation (LRA) source or rotational activation pattern (RAP) source 114. Classified by exemplary spatial-temporal phenotype including. The source of the lesion is one of the promoters that originates from a small area of the heart that expands centrifugally from one point. The RAP source 114 is an irregular region of the heart in which the electrical pulse rotates at least 360 ° around the central region.

FIG. 1 also shows various types of perpetual factors 110, including one type showing ordered conduction delay 116 and another type showing disordered conduction delay 118. Another type of persistent factor 110 shown in FIG. 1 is atrial flutter (AFL) 120 characterized by ordered conduction delay 116, and localized irregular activity characterized by disordered conduction delay 118. Includes (LIA) 122, linear gap 124, and pivot 126 (ie, an electrical pulse that rotates less than 360 ° around the central region). Also, the RAP source 114 is shown as both a promoter 108 and a permanent factor 110. The facilitating factor 108 and the perpetual factor 110 are mapped separately, for example, to facilitate the identification of the facilitating factor type and / or the perpetual factor type and to provide an efficient and accurate determination of the potential ablation ROI.

The mapping and characterization of facilitating factors 108 and persistent factors 110 also reveals one or more additional factors that could potentially contribute to AF, or the expression of AF substrates (ie, the AF process itself) and / or AF processes. It can also be based on potentially characteristic parameters. For example, AF parameters or AF factors used to identify a potential lesion source 108 include omnidirectional activation expansion of activation from a single point, a focal source that initiates after an excitatory gap (eg, an excitatory gap). ), Local rapid excitement (eg, short cycle length and very predominant frequency) and breakthroughs (eg, pulmonary veins (PV), free and transwalled, endocardial and epicardial), and Examples include a microreentry circuit that manifests as a lesion source and a short radius reentry circuit that can be manifested as a facilitator 108 depending on the particular anisotropic structure of the central obstruction.

AF parameters or AF factors used to map and identify the RAP source 114 include, for example, a repeat cycle, a rotor expressible as a promoter source 108, a structure (eg, localized or distributed). Short radius reentry circuits that can be expressed as either facilitator 108 or permanent factor 110, depending on the specific anisotropy structure of the target or functional anisotropy and the central obstacle.

AF parameters or AF factors used to map and identify the persistent factor 110 include, for example, extended (increased) path length, anatomical (pathological) block line, fibrillation, stable function. Target block lines (eg, regions where the incapacity persists), critical areas (eg, the shortest path around the block line> path length) and fibrillation conduction factors (eg, separated waves, reentry circuit factors). ..

FIG. 2 is a block diagram illustrating an exemplary system 200 used to determine the AF ROI for ablation, as used in the embodiments disclosed herein. As shown in FIG. 2, the system 200 includes a catheter 202, a processing device 204, and a display device 206. Catheter 202 includes an array of catheter sensors (eg, electrodes), each configured to detect electrical activity (electrical signals) in a region of the heart over time. When IC ECG is being performed, each electrode detects electrical activity in the area of the heart in contact with the electrodes. The system 200 also has an extracardiac sensor 210 (eg, an electrode on the patient's skin) configured to detect electrical activity in the heart by detecting electrical changes on the skin due to the electrophysiological pattern of the heart. )including.

The detected IC ECG signal and the detected extracardiac signal are processed by the processing device 204 (for example, recording, filtering, subdivision, mapping, coupling, processing, etc. over time) and displayed on the display device 206.

Embodiments may include any number of sensors 210 used to detect ECG signals, including sensors used to detect IC ECG signals and extracardiac ECG signals. For brevity, the systems and methods described herein describe the detection and use of IC ECG signals. However, it should be noted that embodiments can utilize IC ECG signals, or extracardiac ECG signals, or combinations of both IC ECG signals and extracardiac ECG signals.

The processing device 204 may include one or more processors, each configured to process an ECG signal. Each processor of the processing device 204 records the ECG signal over time, filters the ECG signal, subdivides the ECG signal into signal components (eg gradient, wave, complex), maps the ECG signal, and performs the ECG signal. It can be configured to combine information, map it, process the mapping information, and so on.

The display device 206 includes one or more displays, each configured to display an ECG signal, ECG signal information, a map of the AF process, and a map showing the spatial-temporal manifestations of the AF process. It's fine.

The catheter sensor 208 and the extracardiac sensor 210 can communicate with the processing device 204 by wire or wirelessly. The display device 206 can also communicate with the processing device 204 by wire or wirelessly.

3A and 3B are part of a flow chart illustrating an exemplary method 300 for determining a potential ablation ROI. Method 300 uses a mapping classification method that includes an IC ECG layer, a pretreatment layer, a LAT detection layer, a map division layer, a map processing layer, and a map interpretation layer from the center to the outside.

FIG. 3A shows a portion of the exemplary method 300. As shown in block 302 of FIG. 3A, method 300 comprises obtaining an IC ECG signal indicating electrical activity in a region of the heart as part of the IC ECG layer. The IC ECG signal obtained at block 302 is obtained, for example, from one of a number of electrodes in contact with different regions of the heart. After obtaining the IC ECG (302), the method 300 includes a step of pretreating the obtained ECG signal as part of the pretreatment layer, as shown in block 302 of FIG. 3A. This preprocessing may include execution of one or more algorithms, such as cancellation of ventricular farfield signals, baseline correction, and noise reduction. Examples of ventricular farfield detection include spatial averaging (SAM), time averaging (TAM), system identification (SIM), and principal component analysis (PCA).

For each IC ECG signal obtained in block 302, one or more LATs of the corresponding preprocessed IC ECG signals are detected in block 304. The LAT quality (indicated as LATQ in FIG. 3A) for each signal is determined at block 306 as part of an exemplary LAT detection layer. The AF complexity of the signal (denoted as CPLX in FIG. 3A) is determined at block 308.

As shown at determination point 310, method 300 includes determining whether to reposition the catheter based on the LAT quality and AF complexity of the signal. A typical feature of high quality IC ECG is that there is little baseline swell (eg, low baseline vs. IC ECG RMS amplitude, limited ventricular far-field potential vs. IC ECG RMS amplitude). The IC ECG signal is characterized by confinement, separated by identifiable atrial complexes during AF (eg, isoelectric segments repeating slopes (50-200 ms intervals, median about 150 ms)). (~ 50ms) complex). The characteristics of a high quality complex usually have considerable amplification within the complex, and a steep downward slope (upward slope). The features of the IC ECG signal can be combined into a single measurable feature or parameter (eg, having a measurable 0% to 100% value) to specify LAT quality. The LAT quality can be compared to the AF complexity to determine whether to reposition the catheter.

In some embodiments, the ability to map AF with respect to the degree of AF complexity defines quality. Determining whether to reposition the catheter is based on generating a map and using the generated map to see if the degree of range of the mapping electrodes meets (eg, matches) the degree of AF complexity. , AF may include determining if it can be mapped (eg, sufficient to map). The ability to map AF with respect to the degree of AF complexity may include satisfying map thresholds (eg, sufficient, reliable). A single parameter (ie, mapping range) is used to specify the extent of the mapping electrode range. Examples of features to be combined to define the mapping range are (1) contact of the mapping electrode (eg, contact with the active tissue (wall) associated with the covered area and accuracy of the LAT), (2) of the electrode. Resolution (eg, distance between electrodes including mean, minimum and maximum, and distance and radius of sensitivity of the electrodes), (3) quality of IC ECG provided by the detection algorithm and related annotations.

AF complexity can include activation complexity while AF produces wave decomposition (block lines), fusion and wave curvature. Therefore, given a certain degree of AF complexity (eg, measured along the y-axis), the mapping range (including the quality of the signal and annotation determined along the x-axis) maps the AF complexity. The map may be determined as a (eg, reliable or sufficient) map that can be used to map AF if sufficient. Otherwise, the reliability of the map may be compromised or inadequate.

The signal may then be analyzed using a reliable or sufficient map to determine if the catheter should be repositioned. If the catheter repositioning is determined at decision point 310, the catheter (eg, catheter 202) is repositioned at block 312 and a new IC ECG signal is obtained at block 302. If it is determined at decision point 310 that the catheter should be rearranged, method 300 continues to "point A" 313 (shown in FIGS. 3A and 3B).

FIG. 3A shows the acquisition of a single IC ECG signal for brevity. However, in practice, multiple signals are obtained for each of the plurality of electrodes in contact with the heart. Each IC ECG signal obtained in block 202 and one or more LATs detected in block 204 for each signal are received at "point A" 313.

FIG. 3B shows an exemplary method that can be used to determine the ROI of potential ablation. As shown in FIG. 3B, the electricity of the AF substrate (shown as AF substrate 314 in FIG. 3B) using each IC ECG signal obtained and one or more LATs detected for each signal-. Generates a map of the AF process, including the physical state, and a map representing the spatial-temporal manifestations of the AF process (shown as AF process 316 in FIG. 3B) as part of an exemplary map partitioning layer.

For example, with respect to the AF substrate 314 shown in FIG. 3B, the detected one or more LATs are used to independently determine one or more factors or parameters that may contribute to AF. The left side of FIG. 3B includes subsequent LAT 318, initial excitement (quickness) 324, and RS ratio 320 and subdivision 322 (eg, subdivided potential diagram) while collecting information over a predetermined time window. Demonstrates how to characterize an AF substrate by assessing mean intervals (eg, cycles) based on differences in morphological aspects of IC ECG. For example, using the detected LAT, cycle information at block 318 (eg, cycle length), and speed information at block 324 (eg, earliest excitement arrival time, early facilitator starting after excitement gap). Is determined independently. Also, using each IC ECG signal, the RS complex information 320 (eg, the ratio of the R wave to the amplitude of the S wave) and the subdivision information 322 of the IC ECG signal (eg, gradient information, eg, relevant). Information indicating the incidence of source behavior, which is shown as the earliest excitement from one of multiple electrodes, such as the rate at which an electrode is activated faster than an adjacent electrode), And CV block information 326 (eg, conduction (ie, progression) of an electrical impulse through the heart, such as conduction time (CT), path length (ie, distance) and CV of the electrical pulse in which the electrical pulse travels a distance in the heart). (Information indicating the delay or block of) is determined individually.

As shown, the facilitator map 328 is generated from cycle information 318, speed information 324, and RS complex information 320. Permanent factor map 330 is generated from CV block information 326 and subdivision information 322. As shown, the information used to generate the facilitator map 328 and the information used to generate the persistent factor map 330 were combined (eg, overlaid in one map or one display area). Generates a combined facilitator / perpetual factor map 334 (map or adjacent map). The combined facilitator / permanent factor map 334 can then be used to determine one or more ablation ROI 350s (eg, processed as part of an exemplary map processing layer). ..

For the AF process 316 shown in FIG. 3B, the detected one or more LATs are used to generate the activation / wave map 336, CV map 338 (eg, CT of electrical pulse, path length and / or CV). A map) and a block map 344 (eg, a map generated from information indicating a block in the conduction of a signal) are independently generated.

The activation / wave map 336 shows, for example, the percentage of activation waves detected by the corresponding electrode activated earlier than the adjacent electrode, but limited by the adjacent electrode activated by the same wave. May include a map representing the incidence of source behavior that presents the earliest excitation of one of a plurality of electrodes restricted by the same wave. The activation / wave map 336 may also include, for example, a map representing the rate of occurrence of electrode positions associated with the initiation of fibrillation waves.

Each IC ECG signal is used to independently generate a voltage map 342 and a subdivision map 340. The information used to generate maps 336-344 is combined to provide a combined map or video 346. In some embodiments, the information used to generate the activation / wave map 336 and voltage map 342 is combined to generate a combined activation / wave / voltage map or video to generate a CV map 338, block map 344, And the information used to generate the subdivision map 340 are combined to generate a combined CV / block / subdivision map or video. At block 348, the combined map / video 346 is analyzed (eg, read by medical personnel as part of an exemplary map reading layer) to determine the ROI to ablate at block 350. The combined map / video 346 represents the spatial-temporal manifestation of the easily visible and readable AF process, facilitating an efficient and accurate process for determining the ROI for ablation. The determined ROI may be represented (eg, displayed) by, for example, a color, a 3D cross section on a 4D map, an icon (eg, a dynamically changing icon), and the like.

In some embodiments, both the combined facilitator / persistent factor map 334 and the combined map / video 346 are used to determine the ROI for the ablation 350. For example, the ROI for ablation 350 can be determined using the combined facilitator / perpetual factor map 334 without using the combined map / video 346 (eg, viewing, analyzing).

In some embodiments, the quality map 332 is also used in combination with the combined facilitator / persistent factor map 334 and / or the combined map / video 346 to determine the ROI for the ablation 350. Using quality map 332, generated maps related to AF substrate 314 (eg, facilitator map 328, perpetual factor map 330, and facilitator / perpetual factor map 334), as well as generation related to AF process 316 parameters. The reliability of the generated maps (eg, activation / wave map 336, CV map 338, subdivision map 340, voltage map 342, and block map 344) is determined. If the quality of the quality map is low, the generated map is unreliable and specifies an ablation ROI 350 compared to the case where the quality map shows a high quality signal (IC ECG) as the basis for the generated map. That should be considered a high level of attention (eg, by a doctor).

In some embodiments, determining the ROI for ablation 350 specifies or selects one or more ablation sites to be used to determine one or more ROIs for ablation. include. For example, the ablation site may be designated or selected from the evidence of the facilitator and the evidence of the perpetual factor (eg, determined from the facilitator map 328, the perpetual factor map 330, or the combined facilitator / perpetual factor map 324). The ablation ROI 350 may be determined based on the site.

The maps and mapping techniques disclosed herein potentially reduce (i) AF map analysis training time, (ii) time to determine ROI for ablation, and (iii) AF. Success rate of ablation for ablation aimed at facilitating efficient map interpretation and (iv) isolation and disappearance of facilitators, pathway extension, reentry circuits, fibrillation conduction, and slowing down fragmented potentials. To increase.

The techniques of the invention presented herein incorporate subdivisions to efficiently determine the exact ROI targeted for ablation.

FIG. 4 is a high-level block of the process for generating an ablation ROI (shown in FIG. 3B) based on the promoter map 328 (cycle, speed, RS) and persistent factor map 330 (block and subdivision). The figure is shown. From these facilitator maps 328 and perpetual factor maps 330, parameters 401 related to facilitators and parameters 402 related to perpetual factors are derived. Parameters 401 related to the facilitator include cycle length 403 (short cycle, fast repeat), speed 404 (fast excitement to facilitate the AF process), and RS ratio 405 (S wave dominance). Parameters 402 related to the permanent factor include block 406 (block line) and subdivided potential 407 exhibiting non-uniform conduction. Both the facilitator-related parameter 401 and the perpetual factor-related parameter 402 are further processed and combined with the facilitator evidence 408 (De) and the perpetual factor evidence 409 (Pe). Finally, using the facilitating factor evidence 408 and the persistent factor evidence 409 (as two categories of arrhythmogenic Comel's triangles), either the facilitating factor process or the persistent factor process, or both. Derives a potential ROI for ablation 350, acting as.

FIG. 5 shows examples of facilitator / permanent factor maps 334 and temporal activation / subdivision maps (52, 53). The upper right panel of FIG. 5 is the facilitator / perpetual factor map 334, where dot 510 is an exemplary region with increased facilitator evidence (De 408 shown in FIG. 4) that exceeds a predetermined threshold. The dot 520 represents an exemplary region of evidence (Pe> T) (Pe 409 shown in FIG. 4) of the increased permanent factor.

FIG. 6 shows an overview of the technique of the invention as a flow chart showing AF mapping for specifying the ROI for ablation using subdivision analysis. As shown in FIG. 6, in step S61, template matching is performed on the IC ECG using a template from the template library 701 that includes a synthetic single potential and a short double potential that match the acquired IC ECG signal 302. implement. The creation of the template library 601 is described in more detail below with reference to FIGS. 7-10.

In step S62, the subdivision window is found using the LAT from step S61 that matches the template. This is discussed in detail below. See FIGS. 11 and 12. Note that non-subdivided windows are not analyzed and are considered for contact 332 or quality analysis.

In step S63, the subdivision window is used and the non-subdivision window is used as contact to analyze the subdivision and create a subdivision IC ECG. An embodiment of this analysis will be described in more detail below with reference to FIG.

Detection of subdivision is based on a filtering step that detects and removes non-subdivided IC ECG potentials, including single potentials, short dual potentials and long dual potentials. FIGS. 7-11 show AF mappings for designating an ablation ROI indicating the detection of subdivided IC ECGs.

FIG. 7 shows the distribution and sample 701 of various types of pourbaix diagrams taken from one of a number of electrodes in contact with different regions of the heart (see FIG. 3A, block 302). These may include a single potential 702, a short double potential 703, a long double potential 704 and a subdivided potential diagram 705. All swatches 701 are used as a reference for creating a template library 601 with a synthesized single potential 801 and a short double potential 802.

In FIG. 8, the combined single potential 801 has six feature points 81 (eg, the filled circle shown in the lower left of FIG. 8) connected by piecewise tertiary spline interpolation 82, and bandwidth reduction (<250 Hz). Specified by. In one embodiment, nine ratios of R-wave and S-wave amplitudes (R-RS-S waves) are created as a combined single potential 83. In one embodiment, the synthesized different single potentials 83 vary in amplitude (A) and duration (milliseconds), and further perform bandwidth reductions such as cutoff with a 250 Hz low pass filter (LPF). Created by. This will be described in more detail below. As shown in the circle 85 on the right of FIG. 8, the combined potential 83 can be superimposed on the acquired matching single potential 702. As shown, for each synthetic potential, they do not always match.

FIG. 9 shows template matching for creating a combined double potential such that when two combined potentials (primary potential 83 and secondary potential 84) are selected and used, a combined short double potential is created. Further details about. The primary potential 83 remains unchanged, but the secondary potential 84 adjusts the amplitude (A) and shifts the time (t) before combining with the primary potential 83 to create a short dual potential. Both are possible. As shown in FIG. 9, first, all combinations of the two single potentials are selected in order to create a synthetic set of short dual potential templates (S91). The components of the primary potential 83 can be used without further manipulation. The following measures may be performed on the constituents of the secondary potential 84. First, the amplitude adjustment (S92) of the secondary component is carried out. Next, a time shift (S93) is performed with respect to the relative delay time of the secondary component passing through the recording electrode. Finally, the weighted and delayed single, primary and secondary components are summed (S94) and 8,748 template sets are input. In one embodiment, the template library standard may include a sequence of two templates from a single potential set such that nine ratios, such as R, Rs, RS, fS, S, etc., are created. In one embodiment, amplitude adjustment (eg, 0 or 50% amplitude reduction) may be used. In one embodiment, the time shift of the secondary component may be, for example, any of 4, 8, 12, 16 ms.

FIG. 10 uses parameters with amplitudes (AR, AS) of 0, 25, 50, 75 and 100%, durations ( _{R Dur} , _{S Dur} ) of 4, 9, 15 ms, and RS _Dur of 2 ms. The library of the synthesized single potential 83 and the short double potential 101 prepared in the above is shown. As shown, 27 single potentials 83 are created by varying the amplitude and subsequently the duration. For example, one single potential is AR = 0, _AS = 0, _{R Dur} = 4 ms, and the second single potential is AR = 25%, _AS = 0, _{R Dur} = 9 ms. Another single potential is AR = 50%, _AS = 0, _{R Dur} = 14 ms, yet another single potential is _AR = 75%, AR = 0, _{R Dur} = 4 ms, and so on. .. These synthesized single potentials 83 and double potentials 101 are stored in a template library and used as a template matching portion for subdivision analysis.

FIG. 11 shows a template matching method including a template library standard for a library of synthesized single potential 83 and short double potential 84. First, a fibrillation potential map (IC ECG) is obtained (S1101). Next, baseline correction is performed (S1102), where the ventricular farfield artifact 111 is acquired. Next, QRS subtraction is performed (S1103) to remove ventricular Farfield artifacts and create a simplified ECG. Next, template matching is performed in the simplified ECG as follows. Create an analysis window and move it over the simplified ECG. In FIG. 11, a window 112 is shown in the center of the simplified ECG, and six "template matching" templates showing templates from the applied template library are also shown. As shown, the first template 112a has a similarity of 0.54 (about 54%). The second template 112b has a similarity of 0.65 (about 65%). The third template 112c has a similarity of 0.63 (about 63%). The fourth template 112d is 0.48 (about 48%), the fifth template 112e is 0.91 (about 91%), and the sixth template 112f is about 0.78 (about 78%). be. Therefore, the window 112 shows the "highest match" with a similarity of 0.91.

After performing template matching, the "highest match", eg, a template with a similarity of 0.91, can be used to create the fibrillation correlogram 113 (S1105). This fibrillation correlogram 113 can be created by calculating the association of the most suitable template (eg, the largest association). Finally, associations of the fibrillation correlogram 113 below a predetermined maximum threshold (S1106), eg 0.4 or less than 0.5, are blanked. Further, the blanked fibrillation correlogram 113 shown in FIG. 11 includes a template number and a detection point for each peak 114.

FIG. 12 shows a graph showing the detection of subdivided IC ECG. Detection of subdivision occurrence can be performed by excluding single and short double potentials using template matching. For example, the detection process finds areas such as 1201 (second column, indicated by an ellipse) where no match is found. These discrepancies 1201 are special and are of interest when determining the ablation ROI 350. Subdivision analysis may be aimed at identifying permanent regions between AFs. Therefore, by combining subdivision and block, the persistent factors shown in the short line 1202 (upper column) in FIG. 12 can be determined.

FIG. 13 shows a graph showing different examples of AF mapping for specifying the ROI for ablation. The fibrillation map (top row), fibrillation potential (center row), and scaleogram (bottom row) obtained from the wavelet decomposition of the fibrillation potential are shown in FIG. Example D displays multiple decomposed waves, epiend decompositions, and delayed and / or staggered conductions used as tools or evidence for positioning subdivision regions.

FIG. 14 shows AF mapping for detecting the occurrence of subdivision in IC ECG. As shown in FIG. 14, a plurality of windows 112 (-200 ms ← + TM detection → + 10 ms) are created around each detection point 114 obtained from template matching (that is, TM detection). Subdivisions are not detected as long as the windows that follow overlap. If non-overlapping windows are detected, the subdivision signal is set to zero.

FIGS. 15 and 16 show an example of AF mapping for detecting the occurrence of subdivision in IC ECG. The graph above (IC ECG) 151 shows the acquired ECG. The following graph 152 shows the correlogram 113 derived according to the above procedure with respect to FIG. The following graph 153 shows the amplitude processing of the root mean square (RMS). The graph 154 below shows that the non-subdivision occurrence and the subdivision occurrence (that is, the subdivision window 112) occur alternately. That is, the graph 154 below shows the subdivision elements of the ECG signal.

Referring to FIG. 16, this graph shows a non-subdivided IC ECG followed by a subdivided IC ECG. The vertical dotted line indicates the transition from the non-subdivided IC ECG to the subdivided IC ECG. In this way, changes in transition can be clearly observed in the IC ECG.

FIG. 17 is a more detailed flow chart of a method for AF mapping to detect the occurrence of subdivision in one embodiment using tilt analysis. The IC ECG subdivision window is input and peak valley detection is performed (S171). The peaks and valleys are output, followed by the positive / negative tilt duration and amplitude calculated (S172). The subdivision slope is output from step S172 and the slope interval, duration and amplitude are used to calculate the duration, amplitude and incidence (S173).

The duration, amplitude and rate of occurrence are then used to calculate the number of subdivisions (NFRAC), the number of farfields (NFFLD) and the number of single potential gradients (NSINGLE) (S174). NFRAC, NFFLD and NSINGLE are output from step S174 and input to S175. In step S175, the number of subdivision evidences (EFRAC), the number of farfield evidences (EFFLD), and the number of single potential evidences (ESINGLE) are calculated. EFRAC, EFFLD and ESINGLE are output from step S175 and input to step S176. In step S176, the determination rule is executed and the subdivided IC ECG is output. In one embodiment, the subdivided IC ECG may be identified if the EFRAC exceeds a predetermined high threshold (eg 90%). In another embodiment, the subdivision IC ECG identifies when EFRAC exceeds another lower predetermined threshold (eg 70%) and both EFFLD and ESINGLE are below a third lower predetermined threshold. May be done.

In yet another embodiment, a predetermined threshold (QUALITYTHRESHOLD), a low gradient amplitude with parameters, such as SLOPEAMPLOW {frac, fld, single}, a high gradient amplitude with parameters (SLOPEAMPHIGH {frac}), and / or parameters. Data such as the tilt duration having (SLOPEDUR {frag, threshold, single}) can be input to step S174. In this embodiment, this data can be used to calculate the number or incidence of NFRAC, NFFLD, NSINGLE.

Subdivision maps can include two categories: amplitude and spacing. The subdivided amplitude map shows the incidence of electrode positions associated with the subdivided potential. The subdivision interval map shows the incidence of electrode positions associated with the subdivided potential.

FIG. 18 shows S171 of FIG. 17, that is, an embodiment of peak valley detection. As shown in FIG. 18, the tilt analysis can include displaying the peaks 181 and valleys 182 of the acquired ECG 302. The dotted rectangular box 183 contains "three sets" of slope values for valleys 182, peaks 181 and valleys 182, respectively. Further, each of the rectangular boxes 183 has a tilt amplitude as a height 262 and a tilt duration as a width 263. This is further illustrated in FIG.

FIG. 19 shows embodiments of S172 and S173 relating to the calculation of positive / negative gradient amplitude duration and amplitude. FIG. 26 shows a dotted rectangular box 183 of FIG. 18 as a solid box 191. As shown in FIG. 18, the rectangular box of FIG. 19 shows an inclination such that the height 262 of each box is the inclination amplitude and the width 263 of each box is the inclination duration. It should be noted that for subdivision analysis, as discussed herein, the downward tilt is of interest and the upward tilt is usually ignored.

FIG. 20 is a diagram of an embodiment of S174 relating to the classification of tilt characteristics, in which two determination rectangles are presented. These are determination rectangles that indicate tilt information. As shown, the two rectangles 2001, 2002 each include a smaller rectangle indicating the type of tilt, such as farfield (FFLD), noise, primary (PRIM) and secondary (SECU) components. The tilt parameter threshold is defined to position a rectangle, i.e., the relevant negative tilt duration x amplitude 2001 and negative tilt x negative tilt amplitude 2002 in order to clearly select one of the tilt types. Will be done. For example, the tilt duration can be in the range of 0 ms to 100 ms, as shown in rectangle 2001, while the tilt can be in the range of 0 to 1 mV / ms, as shown in rectangle 2002. Tilt characteristics are discussed in more detail below.

FIG. 21 shows four graphs. From top to bottom, these graphs are potential diagram 2101, amplitude 2102, duration 2103 and slope 2104. Graph 2101 above shows the detected IC ECG and tilt timing, along with tilt classification (PRIM, SECI or FFLD) based on tilt characteristics (tilt amplitude, duration and tilt), where these tilt characteristics are thresholds. And are shown separately in the three graphs 2102, 2103 and 2104 below. The graph 2104 below shows the time stamp of the tilt (for example, the tilt occurrence rate). Each graph includes a primary slope 1, a secondary slope 2 and a farfield slope 3. This data is used to make decisions about the ECG and whether the ECG involves subdivision, as discussed in more detail below.

FIG. 22 shows the evolution from the type of tilt to the possible types. In one embodiment, the primary tilt 2201, secondary tilt 2202 and Farfield tilt 2203 are single potential 2220, short double potential 2221, long double potential 2222, subdivided complex 2223, Farfield 2224 and near Farfield. It can evolve into a type of potential consisting of 2225. Progress from the primary slope 2201 and the secondary slope 2202 is first carried out using the time gate 2204. The time gate 2204 processes the tilt within the time limit, which time limit can be, for example, 15 ms and 50 ms, as shown in FIG. However, these durations are just examples and other timings may be used. Both the primary tilt 2201 and the secondary tilt 2202 are input to the time gate 2204, and based on these time limits, initial decisions are made to convert the tilt to potential. For example, a primary and secondary slope with a time limit of 50 ms has two slope groups, ie, a single slope 2205, or> two, depending on whether the slope is one or grouped. It can be one of 2208 slope groups. Further, the primary tilt 2201 and the secondary tilt 2202 having a time interval of 15 ms are a long (interval exceeding 15 ms) group 2207 or a short group 2206 (interval of 15 ms or less) (for example, two tilt groups S (short) 2206). , Or can be grouped into two inclined groups L (long) 2207). Groups with more than two tilts and an interval of less than 50 ms are grouped into> two tilt groups 2208. After processing at time gate 2204, the tilt evolves into an electric potential. As shown, a single slope is considered to have a special relationship. These evolve into a single potential 2220. The two tilt groups S2206 are usually multiplied by 3 × 3 and develop into a short double potential 2221. The two tilted groups L 2227 evolved into a long dual potential 2222 and> the two tilted groups 2208 evolved into a subdivided composite potential 2223, which are special and special confirmations as discussed herein. receive. The potentials are grouped into continuous slopes with intervals of less than 50 ms and analyzed as a type of slope for each slope group. These potentials that are not in the group are output as non-contact 2209 and are not subject to further analysis. Usually, the group size is (2,> 2).

FIG. 23 further shows the time gates and time groupings of the primary and secondary slopes. As shown in FIG. 23, the non-contact potential created by the time gate 2209 can be analyzed as follows. For non-contact potentials, a 3 × 3 spatial-temporal time window is analyzed and the FFLD gradient is annotated. Non-contact evidence is collected by investigating the 3x3 neighborhood for farfields and additional non-contact potentials. Further, the tilt annotation in the window (t ± W) is analyzed for the primary tilt. This analysis can reveal whether the primary tilt is not seen in the central electrode IC ECG or the primary tilt is seen in the central electrode IC ECG. The lack of a primary tilt is based on the fact that only farfield tilt is found in the adjacent electrodes of the non-contact evidence and the non-contact evidence, and that the primary tilt is found in the adjacent electrodes of the non-contact evidence. .. Finding the primary tilt of the central electrode in the IC ECG is based on the evidence of the Farfield potential and the simultaneous primary tilt found in the adjacent electrodes of the non-contact evidence.

FIGS. 24 and 25 show two examples of grouping, further showing a single slope 2205, two slope groups 2206, a long double slope group 2207, and> two slopes 2208 (as defined above). These figures show graphs of potential diagrams 2401, 2501, amplitudes 2402, 2502, durations 2403, 2503, and slopes 2404, 2504, respectively, from top to bottom. Each includes a primary tilt 1, a secondary tilt 2 and a farfield tilt 3. 24 and 25 further show the neighborhood groups discussed further below.

FIG. 26 shows a spatial-temporal analysis of the identified slopes represented as rectangles. The matrix on the left, the set of circles, indicates the topological position of the eight adjacent electrodes labeled 1-8, and C (ie, the central electrode). On the right side of FIG. 26, a series of tilt records is shown. Top record 261 shows the tilt of the central electrode C, where the rectangle represents the amplitude and duration of the tilt. As mentioned above, the tilt amplitude 262 (A) is shown as the height and the tilt duration 263 (D) is shown as the width. Records 1-8 below show the same information about the other eight adjacent electrodes 1-8 surrounding the central electrode C. For example, the outputs of electrodes 1 and 8 are shown in FIG.

Figures 27-29 show the spatial-temporal tilt analysis of AF mapping that can be used to provide further evidence as to whether the acquired ECG 302 and each portion thereof is subdivided. The spatial-temporal relationship between the tilt of the central electrode C and the tilt of the adjacent electrodes 1-8 is evaluated. The spatial-temporal relationship between the tilt 261 of the central electrode and the tilt 264 in each of the IC ECGs of the adjacent electrodes is identified.

FIG. 27 shows the tilt of the central electrode 261 as a graph of the acquired ECG signal 302 conducted and electrically strained. The dotted box indicates a search window for either conduction 271 (wide window) or electrical tension 272 (narrow window) relationships. The conduction relationship 271 includes elements within the spacing limit, within the conduction range, and the corresponding tilt profile. The electrical tension relationship 272 includes a Farfield tilt profile and is instantaneous. The width of the conduction window 263 usually depends on the conduction velocity and the distance from the center to the adjacent electrode. The greater the relationship that can be formed between the central electrode C and the eight adjacent electrodes 1-8, the stronger the evidence for correct annotation of the tilt of the central electrode C.

FIGS. 28 and 29 show specific examples of conduction relationships, electrical tension relationships, and combinations of electrical tension and conduction between the tilt profile 261 of the central electrode and the tilt profile of one of the adjacent electrodes.

FIG. 28 shows a graph for determining the inclination relationship between the central electrode C and the adjacent electrodes 1 to 8. Both conduction and electrical tension relationships have shown increased evidence that the primary gradients tested are related to a single potential. As shown in the graph, the evidence for a single potential is 1) the relationship of conduction gradient with the adjacent electrode (top two graphs); 2) the relationship of electron gradient with the adjacent electrode (middle two graphs); and 3 ) Increases in the case of a combination of conduction and electronic properties for the block (bottom two graphs). Line 281 shows the time travel of the slope near the center in the window and shows their conduction relationship.

FIG. 29 shows the furfield tilt associated with electrical tension (top) or primary tilt (bottom). Evidence of Farfield potential can be increased in the case of the three factors shown. The first factor can be the relationship between the adjacent electrodes and the electrical tension gradient with the gradient showing one maximum single potential. It should be noted that this factor can be based on either the initial characteristics of the slope (T ^* , E ^* ) or the result of the earlier allocation of the slope type (T, E). The second factor can be either FF, as shown in the upper two graphs 2901, 2902, or only a single potential, as shown in the lower two graphs 2903, 2904. Ultimately, if only the electron tilt relationship is found, the property is (temporarily) a non-contact electrode or Farfield (eg, ventricle). The right side of FIG. 29 graphically shows the spatial differences between the measurements of two different electrode groups 2905.

It should be understood that many changes are possible based on the disclosure herein. The features and components in a particular combination have been described above, but each feature or component may be used alone without other features and components, or in various combinations or without combinations with other features and components. can do.

The methods provided include implementation on a general purpose computer, processor, or processor core. Suitable processors include, for example, general purpose processors, special purpose processors, conventional processors, digital signal processors (DSPs), multiple microprocessors, one or more microprocessors that work with DSP cores, controllers. , Microcontrollers, Applied Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) Circuits, Any Other Type of Integrated Circuits (ICs), and / or State Machines. Such processors are manufactured by configuring a manufacturing process that uses the results of processed hardware description language (HDL) instructions and other intermediary data, including netlists (such instructions that can be stored on a computer's readable medium). can do. The result of such processing can subsequently be mask work used in a semiconductor manufacturing process to manufacture a processor that implements the methods described herein.

The methods or flowcharts provided herein can be implemented in a computer program, software, or firmware embedded in a non-temporary computer-readable storage medium for execution by a general purpose computer or processor. Examples of non-temporary computer-readable storage media include ROM, random access memory (RAM), registers, cache memory, semiconductor storage devices, magnetic media such as internal hard disks and removable disks, magnetic optical media, and CD-. Examples include optical media such as ROM discs and digital general-purpose discs (DVDs).

[Implementation mode]
(1) A method of determining a region of interest for cardiac ablation using subdivision.
A step of detecting an electrocardiogram (ECG) signal via a plurality of sensors, wherein each ECG signal is detected via one of the plurality of sensors and indicates the electrical activity of the heart.
A step of determining one or more local excitement arrival times (LATs) for each of the plurality of ECG signals, each of which determines the time of activation of the corresponding ECG signal. Show, process and
One or more driver maps and one or more persistent factor maps based on the determined one or more LATs of each of the plurality of ECG signals. Perpetuator maps), wherein the one or more promoter maps and the one or more permanent factor maps represent the electrical activity of the heart, respectively.
The process of deriving parameters from the facilitating factor map and the persistent factor map using at least subdivision,
The process of processing the derived parameters and combining them with the evidence of facilitators and the evidence of persistent factors.
A method comprising the step of determining the region of interest for cardiac ablation according to the evidence of the facilitator and the subdivision used to derive the evidence of the perpetual factor.
(2) A step of performing the subdivision by filtering the LAT and removing the non-subdivided LAT containing a non-subdivided single potential, a short double potential and a long double potential.
The process of finding a subdivided window using the filtered LAT and
The method according to embodiment 1, further comprising a step of creating a subdivided ECG using the subdivided window.
(3) The method of embodiment 1, further comprising the step of displaying the subdivision with respect to voltage and time using tilt analysis.
(4) A step of detecting peak valleys by detecting peak valleys in the subdivision window, and a step of detecting peak valleys.
The process of calculating the subdivision slope of the detected peaks and valleys, and
The process of calculating the occurrence rate using the detected peaks and valleys,
Using the incidence, a step of calculating the incidence fractionation far field for a single potential gradient, and
The process of calculating evidence number data and
The method according to embodiment 3, further comprising a step of executing a determination rule and outputting the subdivided ECG based on the determination rule.
(5) A step of converting the tilt into an electric potential using a time gate, including time grouping of the primary tilt and the secondary tilt.
A step of grouping the potentials into a group of continuous slopes within a predetermined interval, and
The method according to embodiment 1, further comprising a step of analyzing the potential as a type of gradient according to the grouping.

(6) The size of the group is 2, wherein the group includes a single tilt, a short double tilt, a long double tilt and two tilts, and the predetermined interval is 50 ms, according to embodiment 5. the method of.
(7) The method according to the first embodiment, further comprising a step of displaying the region of interest on a display device.
(8) A system that determines the region of interest for cardiac ablation using subdivision.
A plurality of sensors, each of which is configured to detect one of a plurality of electrocardiogram (ECG) signals over time, each ECG signal indicating a plurality of electrical activity of the heart. With the sensor
A processing device that includes one or more processors.
For each of the plurality of ECG signals, determining one or more local excitement arrival times (LATs), each of which indicates the excitement arrival time of the corresponding ECG signal.
By generating one or more facilitator maps and one or more persistent factor maps based on the determined one or more LATs for each of the plurality of ECG signals. That the one or more promoter maps and the one or more permanent factor maps each represent the electrical activity of the heart.
Deriving parameters from the facilitator and persistent factor maps using at least subdivision,
The derived parameters can be processed and combined with the evidence of facilitators and the evidence of persistent factors.
A processing device configured to determine the region of interest for cardiac ablation according to the evidence of the facilitator and the subdivision used to derive the evidence of the perpetuating factor.
Display devices and systems, including.
(9) The processing device is
Performing the subdivision by filtering the LAT to remove non-subdivided LATs containing non-subdivided single potentials, short double potentials and long double potentials.
Finding subdivision windows using the filtered LAT and
The system according to embodiment 8, further configured to create and perform subdivision ECGs using the subdivision window.
(10) The processing device is
8. The system according to embodiment 8, further configured to display said subdivisions with respect to voltage and time using tilt analysis.

(11) The processing device is
Peak valley detection is performed in the subdivision window to detect peaks and valleys, and
To calculate the subdivision slope of the detected peaks and valleys,
Using the detected peaks and valleys to calculate the incidence,
Using the rate of occurrence, to calculate the rate of occurrence subdivision farfield for a single potential gradient,
Calculating evidence number data and
The system according to embodiment 10, further configured to execute a determination rule and output the subdivided ECG based on the determination rule.
(12) The processing device is
Converting an electric potential into an electric potential using a time gate, including time grouping of primary and secondary inclines,
Grouping the potentials into groups of continuous slopes within a predetermined interval
8. The system according to embodiment 8, further configured to analyze the potential as a type of tilt according to the grouping.
(13) The 12th embodiment, wherein the group has a size of 2, the group comprises a single tilt, a short double tilt, a long double tilt and two tilts, and the predetermined spacing is 50 ms. System.
(14) The system according to embodiment 7, further comprising displaying the region of interest on the display device.
(15) A computer software product that includes a non-temporary computer-readable storage medium in which computer program instructions are stored, and when the instructions are executed by the computer, the computer receives the instructions.
A step of detecting an electrocardiogram (ECG) signal via a plurality of sensors, wherein each ECG signal is detected via one of the plurality of sensors and indicates the electrical activity of the heart.
A step of determining one or more local excitement arrival times (LATs) for each of the plurality of ECG signals, wherein the LATs indicate the excitement arrival times of the corresponding ECG signals, respectively.
In the step of generating one or more facilitator maps and one or more persistent factor maps based on the determined one or more LATs of each of the plurality of ECG signals. There, the steps and the steps, wherein the one or more promoter maps and the one or more permanent factor maps represent the electrical activity of the heart, respectively.
The process of deriving parameters from the facilitating factor map and the persistent factor map using at least subdivision,
The process of processing the derived parameters and combining them with the evidence of facilitators and the evidence of persistent factors.
A computer software product that allows the step of determining the region of interest for cardiac ablation according to the evidence of the facilitator and the subdivision used to derive the evidence of the perpetuating factor.

(16) A step of performing the subdivision by filtering the LAT and removing the non-subdivided LAT containing a non-subdivided single potential, a short double potential and a long double potential.
The process of finding a subdivided window using the filtered LAT and
The computer software product according to embodiment 15, further comprising a step of creating a subdivided ECG using the subdivided window.
(17) The computer software product according to embodiment 15, further comprising the step of displaying the subdivision with respect to voltage and time using tilt analysis.
(18) A step of detecting peak valleys in the subdivision window to detect peaks and valleys, and
The process of calculating the subdivision slope of the detected peaks and valleys, and
The process of calculating the occurrence rate using the detected peaks and valleys,
Using the rate of occurrence, a step of calculating the rate of occurrence subdivided farfield for a single potential gradient, and
The process of calculating evidence number data and
The computer software product according to embodiment 17, further comprising a step of executing a determination rule and outputting the subdivided ECG based on the determination rule.
(19) A step of converting a tilt into an electric potential using a time gate, including time grouping of primary and secondary tilts.
A step of grouping the potentials into a group of continuous slopes within a predetermined interval, and
The computer software product according to embodiment 15, further comprising the step of analyzing the potential as a type of gradient according to the grouping.
(20) The 19th embodiment, wherein the group has a size of 2, the group comprises a single tilt, a short double tilt, a long double tilt and two tilts, and the predetermined spacing is 50 ms. Computer software products.

Claims (11)

A method of operating a system that determines a region of interest for cardiac ablation using subdivision.
The system performs the following steps and
The step is
A step of detecting an electrocardiogram (ECG) signal via a plurality of sensors, wherein each ECG signal is detected via one of the plurality of sensors and indicates the electrical activity of the heart.
A step of determining one or more local excitement arrival times (LATs) for each of the plurality of ECG signals, wherein the LATs indicate the excitement arrival times of the corresponding ECG signals, respectively.
In the step of generating one or more facilitator maps and one or more persistent factor maps based on the determined one or more LATs of each of the plurality of ECG signals. There, the steps and the steps, wherein the one or more promoter maps and the one or more permanent factor maps represent the electrical activity of the heart, respectively.
In the step of deriving a parameter including the potential of the subdivided ECG signal from the permanent factor map, the potential compares the potential of the ECG signal in the subdivision window with a plurality of potential signal templates, and the subdivision is performed. One of the above templates similar to the ECG signal in the chemical window is selected according to the degree of similarity,
Using the derived parameters, including the step of displaying a map showing the evidence of the facilitating factor and the perpetual factor of the subdivision region.
The region of interest for the cardiac ablation is determined according to the subdivision.
The step is
The step of performing the subdivision by filtering the LAT and removing the non-subdivided LAT containing the non-subdivided single potential, the short double potential and the long double potential.
The process of finding a subdivided window using the filtered LAT and
The process of creating a subdivided ECG using the subdivision window,
With the step of using tilt analysis to display the subdivision for voltage and time
The process of detecting peak valleys in the subdivision window to detect peaks and valleys, and
The process of calculating the subdivision slope of the detected peaks and valleys, and
The process of calculating the occurrence rate using the detected peaks and valleys,
Using the rate of occurrence, a step of calculating the rate of occurrence subdivided farfield for a single potential gradient, and
The process of calculating evidence number data and
A method further comprising a step of executing a determination rule and outputting the subdivided ECG based on the determination rule . The step is
The method of claim 1, further comprising displaying the region of interest on a display device. A system that determines the region of interest for cardiac ablation using subdivision,
A plurality of sensors, each of which is configured to detect one of a plurality of electrocardiogram (ECG) signals over time, each ECG signal indicating a plurality of electrical activity of the heart. With the sensor
A processing device that includes one or more processors.
For each of the plurality of ECG signals, determining one or more local excitement arrival times (LATs), each of which indicates the excitement arrival time of the corresponding ECG signal.
By generating one or more facilitator maps and one or more persistent factor maps based on the determined one or more LATs for each of the plurality of ECG signals. That the one or more promoter maps and the one or more permanent factor maps each represent the electrical activity of the heart.
From the permanent factor map, a parameter including the potential of the subdivided ECG signal is derived, and the potential compares the potential of the ECG signal in the subdivision window with a plurality of potential signal templates, and the subdivision is performed. A processing device and a processing device configured to perform that one of the above templates similar to the ECG signal in the conversion window is selected according to the degree of similarity.
The derived parameters are used to include a display configured to display a map showing evidence of facilitators of subdivisions and evidence of persistent factors.
The region of interest for the cardiac ablation is determined according to the subdivision.
The processing device
Performing the subdivision by filtering the LAT to remove non-subdivided LATs containing non-subdivided single potentials, short double potentials and long double potentials.
Finding subdivision windows using the filtered LAT and
Using the subdivision window to create a subdivision ECG,
Using tilt analysis to display the subdivisions for voltage and time,
Peak valley detection is performed in the subdivision window to detect peaks and valleys, and
To calculate the subdivision slope of the detected peaks and valleys,
Using the detected peaks and valleys to calculate the incidence,
Using the rate of occurrence, to calculate the rate of occurrence subdivision farfield for a single potential gradient,
Calculating evidence number data and
A system further configured to execute a determination rule and output the subdivided ECG based on the determination rule. The system of claim 3 , wherein the display is configured to display the region of interest. A computer software product that includes a non-temporary computer-readable storage medium containing computer program instructions that, when executed by the computer, are transmitted to the computer.
A step of detecting an electrocardiogram (ECG) signal via a plurality of sensors, wherein each ECG signal is detected via one of the plurality of sensors and indicates the electrical activity of the heart.
A step of determining one or more local excitement arrival times (LATs) for each of the plurality of ECG signals, wherein the LATs indicate the excitement arrival times of the corresponding ECG signals, respectively.
In the step of generating one or more facilitator maps and one or more persistent factor maps based on the determined one or more LATs of each of the plurality of ECG signals. There, the steps and the steps, wherein the one or more promoter maps and the one or more permanent factor maps represent the electrical activity of the heart, respectively.
In the step of deriving a parameter including the potential of the subdivided ECG signal from the permanent factor map, the potential compares the potential of the ECG signal in the subdivision window with a plurality of potential signal templates, and the subdivision is performed. One of the above templates similar to the ECG signal in the chemical window is selected according to the degree of similarity,
Using the derived parameters, a step of displaying a map showing the evidence of the facilitating factor and the evidence of the persistent factor of the subdivision region was performed.
Regions of interest for cardiac ablation are determined according to the subdivision and
The step of performing the subdivision by filtering the LAT and removing the non-subdivided LAT containing the non-subdivided single potential, the short double potential and the long double potential.
The process of finding a subdivided window using the filtered LAT and
The process of creating a subdivided ECG using the subdivision window,
Using tilt analysis to display the subdivisions for voltage and time,
The process of detecting peak valleys in the subdivision window to detect peaks and valleys, and
The process of calculating the subdivision slope of the detected peaks and valleys, and
The process of calculating the occurrence rate using the detected peaks and valleys,
Using the rate of occurrence, a step of calculating the rate of occurrence subdivided farfield for a single potential gradient, and
The process of calculating evidence number data and
A computer software product further comprising a step of executing a determination rule and outputting the subdivided ECG based on the determination rule. A method of operating a system that determines a region of interest for cardiac ablation using subdivision.
The system performs the following steps and
The step is
A step of detecting an electrocardiogram (ECG) signal via a plurality of sensors, wherein each ECG signal is detected via one of the plurality of sensors and indicates the electrical activity of the heart.
A step of determining one or more local excitement arrival times (LATs) for each of the plurality of ECG signals, wherein the LATs indicate the excitement arrival times of the corresponding ECG signals, respectively.
In the step of generating one or more facilitator maps and one or more persistent factor maps based on the determined one or more LATs of each of the plurality of ECG signals. There, the steps and the steps, wherein the one or more promoter maps and the one or more permanent factor maps represent the electrical activity of the heart, respectively.
In the step of deriving a parameter including the potential of the subdivided ECG signal from the permanent factor map, the potential compares the potential of the ECG signal in the subdivision window with a plurality of potential signal templates, and the subdivision is performed. One of the above templates similar to the ECG signal in the chemical window is selected according to the degree of similarity,
Using the derived parameters, including the step of displaying a map showing the evidence of the facilitating factor and the perpetual factor of the subdivision region.
The region of interest for the cardiac ablation is determined according to the subdivision.
The step is
The process of converting the tilt to an electric potential using a time gate, including time grouping of the primary and secondary tilts,
A step of grouping the potentials into a group of continuous slopes within a predetermined interval, and
A method further comprising the step of analyzing the potential as a type of gradient according to the grouping. 6. The method of claim 6, wherein the group has a size of 2, the group comprises a single tilt, a short double tilt, a long double tilt and two tilts, and the predetermined spacing is 50 ms. A system that determines the region of interest for cardiac ablation using subdivision,
A plurality of sensors, each of which is configured to detect one of a plurality of electrocardiogram (ECG) signals over time, each ECG signal indicating a plurality of electrical activity of the heart. With the sensor
A processing device that includes one or more processors.
For each of the plurality of ECG signals, determining one or more local excitement arrival times (LATs), each of which indicates the excitement arrival time of the corresponding ECG signal.
By generating one or more facilitator maps and one or more persistent factor maps based on the determined one or more LATs for each of the plurality of ECG signals. That the one or more promoter maps and the one or more permanent factor maps each represent the electrical activity of the heart.
From the permanent factor map, a parameter including the potential of the subdivided ECG signal is derived, and the potential compares the potential of the ECG signal in the subdivision window with a plurality of potential signal templates, and the subdivision is performed. A processing device and a processing device configured to perform that one of the above templates similar to the ECG signal in the conversion window is selected according to the degree of similarity.
The derived parameters are used to include a display configured to display a map showing evidence of facilitators of subdivisions and evidence of persistent factors.
The region of interest for the cardiac ablation is determined according to the subdivision.
The processing device
Converting an electric potential into an electric potential using a time gate, including time grouping of primary and secondary inclines,
Grouping the potentials into groups of continuous slopes within a predetermined interval
A system further configured to analyze the potential as a type of tilt according to the grouping. 8. The system of claim 8, wherein the group has a size of 2, the group comprising a single tilt, a short double tilt, a long double tilt and two tilts, the predetermined spacing being 50 ms. A computer software product that includes a non-temporary computer-readable storage medium containing computer program instructions that, when executed by the computer, are transmitted to the computer.
A step of detecting an electrocardiogram (ECG) signal via a plurality of sensors, wherein each ECG signal is detected via one of the plurality of sensors and indicates the electrical activity of the heart.
A step of determining one or more local excitement arrival times (LATs) for each of the plurality of ECG signals, wherein the LATs indicate the excitement arrival times of the corresponding ECG signals, respectively.
In the step of generating one or more facilitator maps and one or more persistent factor maps based on the determined one or more LATs of each of the plurality of ECG signals. There, the steps and the steps, wherein the one or more promoter maps and the one or more permanent factor maps represent the electrical activity of the heart, respectively.
In the step of deriving a parameter including the potential of the subdivided ECG signal from the permanent factor map, the potential compares the potential of the ECG signal in the subdivision window with a plurality of potential signal templates, and the subdivision is performed. One of the above templates similar to the ECG signal in the chemical window is selected according to the degree of similarity,
Using the derived parameters, a step of displaying a map showing the evidence of the facilitating factor and the evidence of the persistent factor of the subdivision region was performed.
Regions of interest for cardiac ablation are determined according to the subdivision and
The process of converting the tilt to an electric potential using a time gate, including time grouping of the primary and secondary tilts,
A step of grouping the potentials into a group of continuous slopes within a predetermined interval, and
A computer software product further comprising the step of analyzing the potential as a type of gradient according to the grouping. 10. The computer software of claim 10, wherein the group has a size of 2, the group comprises a single tilt, a short double tilt, a long double tilt and two tilts, and the predetermined spacing is 50 ms. product.

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